MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells.

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Bibliographic Details
Title: MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells.
Authors: Hinz S; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA. Electronic address: shinz@coh.org., Grøndal SM; Department of Biomedicine & Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway., Miyano M; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA., Lopez JC; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA., Cotner KL; UC Berkeley-UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, CA, USA., Thomsen T; UC Berkeley-UC San Francisco Graduate Program in Bioengineering, University of California, Berkeley, CA, USA., Chen C; Department of Mechanical Engineering, University of California, Berkeley, CA, USA., Hester EJ; Department of Mechanical Engineering, University of California, Berkeley, CA, USA., Yee LD; Department of Surgery, City of Hope Comprehensive Cancer Center, Duarte, CA, USA., Seewaldt VE; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA., Lorens JB; Department of Biomedicine & Centre for Cancer Biomarkers, University of Bergen, Bergen, Norway., Sohn LL; Department of Mechanical Engineering, University of California, Berkeley, CA, USA., LaBarge MA; Department of Population Sciences, Beckman Research Institute, City of Hope, Duarte, CA, USA; Center for Cancer and Aging Research, City of Hope, Duarte, CA, USA. Electronic address: mlabarge@coh.org.
Source: EBioMedicine [EBioMedicine] 2026 May; Vol. 127, pp. 106241. Date of Electronic Publication: 2026 Apr 23.
Publication Type: Journal Article
Journal Info: Publisher: Elsevier B.V Country of Publication: Netherlands NLM ID: 101647039 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2352-3964 (Electronic) Linking ISSN: 23523964 NLM ISO Abbreviation: EBioMedicine Subsets: MEDLINE
Database: MEDLINE Ultimate
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